De retibus socialibus et legibus momenti

Online Social Networks (OSNs) are a cutting edge topic. Almost everybody --users, marketers, brands, companies, and researchers-- is approaching OSNs to better understand them and take advantage of their benefits. Maybe one of the key concepts underlying OSNs is that of influence which is highly related, although not entirely identical, to those of popularity and centrality. Influence is, according to Merriam-Webster, "the capacity of causing an effect in indirect or intangible ways". Hence, in the context of OSNs, it has been proposed to analyze the clicks received by promoted URLs in order to check for any positive correlation between the number of visits and different "influence" scores. Such an evaluation methodology is used in this paper to compare a number of those techniques with a new method firstly described here. That new method is a simple and rather elegant solution which tackles with influence in OSNs by applying a physical metaphor.Comment: Changes made for third revision: Brief description of the dataset employed added to Introduction. Minor changes to the description of preparation of the bit.ly datasets. Minor changes to the captions of Tables 1 and 3. Brief addition in the Conclusions section (future line of work added). Added references 16 and 18. Some typos and grammar polishe

Copula selection models for non-Gaussian responses that are missing not at random

Missing not at random (MNAR) data poses key challenges for statistical inference because the model of interest is typically not identifiable without imposing further (e.g., distributional) assumptions. Sample selection models have been routinely used for handling MNAR by jointly modelling the outcome and selection variables assuming that these follow a bivariate normal distribution. Recent studies have advocated parametric selection model approaches, for example estimated by multiple imputation and maximum likelihood, that are more robust to departures from the normality assumption. However, the proposed methods have been mostly restricted to a specific joint distribution (e.g., bivariate t-distribution). This paper discusses a flexible copula-based selection approach (which accommodates a wide range of non-Gaussian outcome distributions and offers great flexibility in the choice of functional form specifications for both the outcome and selection equations) and proposes a flexible imputation procedure that generates plausible imputed values from the copula selection model. A simulation study characterises the relative performance of the copula model compared with the most commonly used selection models for estimating average treatment effects with MNAR data. We illustrate the methods in the REFLUX study, which evaluates the causal effect of laparoscopic surgery compared to usual medical management on long-term quality of life in patients with reflux disease. We provide software code for implementing the proposed copula framework using the R package GJRM

Quantitative proteomics reveals tissue-specific, infection-induced and species-specific neutrophil protein signatures

Neutrophils are one of the first responders to infection and are a key component of the innate immune system through their ability to phagocytose and kill invading pathogens, secrete antimicrobial molecules and produce extracellular traps. Neutrophils are produced in the bone marrow, circulate within the blood and upon immune challenge migrate to the site of infection. We wanted to understand whether this transition shapes the mouse neutrophil protein landscape, how the mouse neutrophil proteome is impacted by systemic infection and perform a comparative analysis of human and mouse neutrophils. Using quantitative mass spectrometry we reveal tissue-specific, infection-induced and species-specific neutrophil protein signatures. We show a high degree of proteomic conservation between mouse bone marrow, blood and peritoneal neutrophils, but also identify key differences in the molecules that these cells express for sensing and responding to their environment. Systemic infection triggers a change in the bone marrow neutrophil population with considerable impact on the core machinery for protein synthesis and DNA replication along with environmental sensors. We also reveal profound differences in mouse and human blood neutrophils, particularly their granule contents. Our proteomics data provides a valuable resource for understanding neutrophil function and phenotypes across species and model systems.</p

Quantitative proteomics reveals tissue-specific, infection-induced and species-specific neutrophil protein signatures

Neutrophils are one of the first responders to infection and are a key component of the innate immune system through their ability to phagocytose and kill invading pathogens, secrete antimicrobial molecules and produce extracellular traps. Neutrophils are produced in the bone marrow, circulate within the blood and upon immune challenge migrate to the site of infection. We wanted to understand whether this transition shapes the mouse neutrophil protein landscape, how the mouse neutrophil proteome is impacted by systemic infection and perform a comparative analysis of human and mouse neutrophils. Using quantitative mass spectrometry we reveal tissue-specific, infection-induced and species-specific neutrophil protein signatures. We show a high degree of proteomic conservation between mouse bone marrow, blood and peritoneal neutrophils, but also identify key differences in the molecules that these cells express for sensing and responding to their environment. Systemic infection triggers a change in the bone marrow neutrophil population with considerable impact on the core machinery for protein synthesis and DNA replication along with environmental sensors. We also reveal profound differences in mouse and human blood neutrophils, particularly their granule contents. Our proteomics data provides a valuable resource for understanding neutrophil function and phenotypes across species and model systems.</p

Optimizing Spectronaut Search Parameters to Improve Data Quality with Minimal Proteome Coverage Reductions in DIA Analyses of Heterogeneous Samples

Data-independent acquisition has seen breakthroughs that enable comprehensive proteome profiling using short gradients. As the proteome coverage continues to increase, the quality of the data generated becomes much more relevant. Using Spectronaut, we show that the default search parameters can be easily optimized to minimize the occurrence of false positives across different samples. Using an immunological infection model system to demonstrate the impact of adjusting search settings, we analyzed Mus musculus macrophages and compared their proteome to macrophages spiked withCandida albicans. This experimental system enabled the identification of “false positives” as Candida albicans peptides and proteins should not be present in the Mus musculus-only samples. We show that adjusting the search parameters reduced “false positive” identifications by 89% at the peptide and protein level, thereby considerably increasing the quality of the data. We also show that these optimized parameters incurred a moderate cost, only reducing the overall number of “true positive” identifications across each biological replicate by &lt;6.7% at both the peptide and protein level. We believe the value of our updated search parameters extends beyond a two-organism analysis and would be of great value to any DIA experiment analyzing heterogeneous populations of cell types or tissues.</p

Optimizing Spectronaut Search Parameters to Improve Data Quality with Minimal Proteome Coverage Reductions in DIA Analyses of Heterogeneous Samples

Data-independent acquisition has seen breakthroughs that enable comprehensive proteome profiling using short gradients. As the proteome coverage continues to increase, the quality of the data generated becomes much more relevant. Using Spectronaut, we show that the default search parameters can be easily optimized to minimize the occurrence of false positives across different samples. Using an immunological infection model system to demonstrate the impact of adjusting search settings, we analyzed Mus musculus macrophages and compared their proteome to macrophages spiked withCandida albicans. This experimental system enabled the identification of “false positives” as Candida albicans peptides and proteins should not be present in the Mus musculus-only samples. We show that adjusting the search parameters reduced “false positive” identifications by 89% at the peptide and protein level, thereby considerably increasing the quality of the data. We also show that these optimized parameters incurred a moderate cost, only reducing the overall number of “true positive” identifications across each biological replicate by &lt;6.7% at both the peptide and protein level. We believe the value of our updated search parameters extends beyond a two-organism analysis and would be of great value to any DIA experiment analyzing heterogeneous populations of cell types or tissues.</p

INDIGO : better geomagnetic observatories where we need them

The INDIGO project aims to improve the global coverage of digital observatories by deploying digital magnetometer systems in: i) Observatories where existing analog recording equipment is in need of upgrading. ii) Newly established digital observatories. iii) Existing digital observatories for the purpose of quality control and redundancy. In implementing the project and selecting suitable sites, special attention is paid to parts of the Earth devoid of magnetic observatories, increasing the reliability and long-term operation of existing observatories and cost-effective use of local resources. The Poster reviews the current status of the project. We examine the different steps and initiatives taken since the initiation of INDIGO in 2004 and assess their effectiveness in achieving progress towards our aims of improving global coverage and enhanced data quality

Períodos de actividad y dieta de Dasyprocta punctata (Gray, 1842) (Rodentia; Dasyproctidae) en agroecosistemas con café, San Ramón, Costa Rica

La guatusa Dasyprocta punctata (Gray, 1842) es una especie clasificada como de población estable y presente en distintos hábitats, no obstante, sus hábitos (dieta, periodos de actividad y comportamiento) han sido poco descritos. La presente investigación se basa en determinar los hábitos D. punctata en agroecosistemas con café en Rincón de Mora, San Ramón, Alajuela, Costa Rica. Para ello, se colocaron cuatro cámaras trampa en sitios estratégicos (fuentes de alimentación, madrigueras, cuerpos de agua y transición con el bosque secundario). La revisión de los videos arrojó nuevos hábitos en cuanto a dieta que no se habían registrado para esta especie, incluyendo el consumo de Polyporus sp. Asimismo, se observó que el mayor periodo de actividad anual en el cafetal se da en la etapa fenológica con fruto, mientras que el periodo de actividad diario se amplió el espectro en horas de la noche. De igual forma, se registraron comportamientos ya identificados, donde uno de los más importantes es la dispersión de semillas.The guatusa Dasyprocta punctata (Gray, 1842) is a species classified as having a stable population and present in different habitats, however, its habits (diet, periods of activity and behavior) have been little described. This research is based on determining D. punctata habits in coffee agroecosystems in Rincón de Mora, San Ramón, Alajuela, Costa Rica. For this, four camera traps were placed in strategic places (food sources, burrows, creeks, and transition with the secondary forest). The review of the videos revealed new dietary habits that had not been recorded for this species, including the consumption of Polyporus sp. Likewise, it was observed that the greatest period of annual activity in the coffee plantation occurs in the phenological stage with fruit, while the period of daily activity broadened the spectrum in hours of the night. Similarly, already identified behaviors were recorded, where one of the most important is seed dispersal